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Accident Risk Prediction via Machine Learning by tanish.mmathur is a document available to read on EtoBox.
What is Accident Risk Prediction via Machine Learning about?
This research paper explores accident risk prediction using machine learning techniques, specifically Extra Trees Regressor and XGBoost, to analyze parameters influencing accident occurrences from a dataset of US accidents from 2016 to 2023. The study emphasizes the importance of parameter significance analysis to enhance predictive accuracy, which currently stands at 85%, and aims to inform targeted safety measures. The findings contribute to the development of a web-based prediction system designed to pro
- Author
- tanish.mmathur
- Language
- EN